The current invention is in the field of optimization of the satellite-based navigation, guidance, and control system.
A prior art conventional Navigation, Guidance, and Control (NGandC) system of missiles and space vehicles includes a GPS-based guidance system combined with an Inertial Navigation System (INS). The INS includes an Inertial Measurement Unit (IMU) designed to measure motions of a host vehicle. Specifically, the IMU block measures the swing of the proof mass of its accelerometers to infer translational accelerations of the host vehicle. Similarly, the IMU block measures the movement of the axes of its spinning gyroscopes to calculate rotational rates. Thus, the accuracy of an IMU-derived data is a function of how well motions of its inertial sensors are known and characterized.
In some applications, however (for instance, for a non-thrusted vehicle such as a projectile), the Gs-accelerations are so high (G≈20,000), that the G-unhardened inertial sensors of the IMU system (spinning gyroscopes) fail. The G-hardening is a very expensive process.
On the other hand, a non-thrusted vehicle, such as a projectile, has its ballistic trajectory well-defined.
There is therefore a need in the art for to replace an IMU sensor in a Navigation, Guidance, and Control (NGandC) system by a body of a non-thrusted vehicle itself.
To address the shortcomings of the available art, the present invention provides, for a satellite-based guidance system that uses the body of the non-thrusted vehicle itself as its inertial sensor.
One aspect of the present invention is directed to a method of a satellite positioning system (SATPS)-based guidance of a non-thrusted flight vehicle.
In one embodiment, the method comprises the following steps: (a) estimating a state or a navigation solution of the non-thrusted flight vehicle by solving a set of non-linear equations of the non-thrusted flight vehicle by using a set of Extended Kalman Filter algorithms; (b) updating the state of the non-thrusted flight vehicle by making real time attitude measurements of the coordinates of the non-thrusted flight vehicle by using a SATPS xe2x80x98vectorxe2x80x99 navigational receiver; (c) estimating and updating parameters of predicted trajectory of the non-thrusted flight vehicle by using a Parameter Estimator; and (d) generating a guidance and control signal configured to perform a real time navigation of the non-thrusted flight vehicle by using an External Guidance and Control Module (EGCM).
In one embodiment, the step (a) of estimating the state of the non-thrusted flight vehicle further includes the step (a1) of performing linearization of the set of non-linear equations of motion of the non-thrusted flight vehicle around a nominal trajectory and converting the set of non-linear equations of motion into a set of linearized equations of motion that is solvable by a Standard Kalman Filter method.
In one embodiment, the step (c) of estimating and updating parameters of predicted trajectory of the non-thrusted flight vehicle by using the Parameter Estimator further includes the step of (c1) updating in real time an estimated set of external parameters and an estimated set of internal parameters of the non-thrusted flight vehicle in order to provide the in-flight corrections to initial conditions of the initially predicted trajectory of the non-thrusted flight vehicle, so that the corrected ballistic trajectory of the non-thrusted flight vehicle hits an aimpoint.
In one embodiment, the step (d) of generating the guidance and control signal further includes the steps of: (d1) predicting an impact point by using the predictive proportional navigation (PPN) guidance algorithm; and (d2) generating a control command to the canards and/or fins of the non-thrusted flight vehicle by comparing the predicted impact point with the aimpoint.
In another embodiment, the step (d) of generating the guidance and control signal further includes the step (d3) of calculating the delta velocity required to fly the non-thrusted flight vehicle to the aimpoint by applying correlated velocity algorithm to a correlated velocity, wherein the correlated velocity is generated by aerodynamic forces on control surfaces of the non-thrusted flight vehicle.
Another aspect of the present invention is directed to an apparatus for a satellite positioning system (SATPS)-based guidance of a non-thrusted flight vehicle.
In one embodiment, the apparatus of the present invention comprises:
(a) a set of Extended Kalman Filter algorithms configured to estimate a state or a navigation solution of the non-thrusted flight vehicle by solving a set of non-linear equations of motion of the non-thrusted flight vehicle;
(b) a SATPS xe2x80x98vectorxe2x80x99 navigational receiver configured to update the state of the non-thrusted flight vehicle by making real time attitude measurements of the coordinates of the non-thrusted flight vehicle;(c) a Parameter Estimator configured to estimate and update parameters of predicted trajectory of the non-thrusted flight vehicle; and (d) an External Guidance and Control Module (EGCM) configured to generate a guidance and control signal to perform a real time navigation of the non-thrusted flight vehicle.
In one embodiment, the satellite positioning system (SATPS)-based guidance system of a non-thrusted flight vehicle comprises a GPS-based guidance system, and the SATPS xe2x80x98vectorxe2x80x99 navigational receiver comprises a GPS xe2x80x98vectorxe2x80x99 navigational receiver.